Physics – High Energy Physics – High Energy Physics - Phenomenology
Scientific paper
1996-07-29
Phys.Lett. B396 (1997) 280-286
Physics
High Energy Physics
High Energy Physics - Phenomenology
11 pages, latex, 2 figures.
Scientific paper
10.1016/S0370-2693(97)00124-X
We consider the possibility of using neural networks in experimental data analysis in Daphne. We analyze the process $\gamma\gamma\to \pi^+ \pi^- \pi^0$ and its backgrounds using neural networks and we compare their performances with traditional methods of applying cuts on several kinematical variables. We find that the neural networks are more efficient and can be of great help for processes with small number of produced events.
Ametller Ll.
Garrido Ll.
Talavera Pedro
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